In 2019, Adobe hired a team eleven engineers to collaborate on the new ingestion product I created in Java/Scala, to help make it a scalable solution capable of processing hundreds of billions of records per day.I currently lead two ingestion teams, responsible for ensuring proper system design for new components and features. I practice thorough code reviews, leading in number of comments made and defects found.

For eight years, I’ve worked on Axle (written in C++), a very fast, scalable, flexible database; taking it from a niche product that serves very few people to an enterprise product backing reporting for all of Adobe Analytics and soon Adobe Marketing Cloud. I’ve been consistently recognized that I get as much done as two or three people. Some of my unique accomplishments:● 3x consecutive winner of Garage Week, vs. hundreds of entrants and 80-100 projects ● Led a team to develop an ingestion engine, that can process hundreds of billions of records per day● Key in designing new features: 3 patents in submission for those features.● Cumulative 40% speedup an already hyper-optimized database.● Special ability picking skunkworks projects that deliver value as focal product points 1-3 years later.From Jan 2018 through May 2019, I prototyped a new ingestion engine in Java and Scala, that became the database above from Adobe Experience Cloud Platform. This new product solved a lot of architectural debt issues that we had accumulated as well. I took bold steps to rearchitect/recreate the product.

● Conceived of a way to create report-time tables in Axle, increasing the flexibility of our product, yielding core features that we needed a year or two later.● I managed to speed up the code for a global 9% speedup.● Led the organization on architectures and techniques for reducing coupling in our UI and database portions. Being capable of solving bugs as a junior engineer gave me broad experience to make this valuable contribution.● Main engineer that management turned to 1) diagnose production problems and 2) fix those production problems after they’ve been triaged and diagnosed. I got extremely good at looking at Linux/Unix operating systems issues.

● Investigated, fixed and closed an average of two bugs per day for a total of over 500 bugs. ● Consistently investigated, fixed system errors and memory spikes. Our incident rate reduced by about 95% during my time as a junior engineer improving system stability.

Mined 12 million campaign contribution donations to discover which ones were made by the same people.Created a genetic algorithm to balance virtual machines on servers.

Refactored schema mapping for the database so that it would all be in one concise location that was easier to use and work with.